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SIMULATION OF GROUND VEGETATION DIVERSITY IN BOREAL FORESTS

SIMULATION OF GROUND VEGETATION DIVERSITY IN BOREAL FORESTS. Larisa Khanina 1 , Maxim Bobrovsky 2 , Alexander Komarov 2 , Alex Mikhajlov 2. 2 Institute of Physicochemical and Biological Problems in Soil Science of RAS, Pushchino.

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SIMULATION OF GROUND VEGETATION DIVERSITY IN BOREAL FORESTS

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  1. SIMULATION OF GROUND VEGETATION DIVERSITY IN BOREAL FORESTS Larisa Khanina1, Maxim Bobrovsky2, Alexander Komarov2, Alex Mikhajlov2 2 Institute of Physicochemical and Biological Problems in Soil Science of RAS, Pushchino 1 Institute of Mathematical Problems in Biology of RAS, Pushchino IBFRA conf. ‘New challenges in Management of Boreal Forests’ August 28–30 2006 Umeå Sweden

  2. Dynamics of ecosystem and plant species diversity • abiotic parameters(climatic, soil, water, etc.) • temporal parametersof plant populations in different forest zones • spatial parametersof the area and plant populations • availability ofseed sources Forest Ecosystem Modelling

  3. Forest ecosystem modelling forest-soil model(Chertov et al., 1999, Komarov, et al., 2003) EFIMOD FORRUS forest model(Chumachenko et al., 2003) Individual-based models Different levels of forest modelling

  4. Ground Vegetation Ecosystem production Soil features Trees renewal EFIMOD

  5. The first step to calculate dynamics of ground vegetation diversityat a level of forest stand on a base of · State Forest Inventory Data · Forest simulated results

  6. Our approach plant species functional groups in ground vegetation modelling ecological-coenotic species groups introduced in Nitsenko (1969) derived frommultivariate analysisspecies traits matrix community matrix matrix of environmental factors

  7. Ecological-coenotic groups

  8. To use the groups for modelling dynamics of ground vegetation · to define the dominant group at the initial stepof simulation · to define rules ofthe group switchingaccording to dynamics of the simulated parameters tree species composition, light supply, deadwood, litter, soil C and N pools etc.

  9. At the initial step of simulation Forest Inventory Data Dominant tree in overstorey Dominant species in understorey Dominant groups in ground vegetation Ecological-coenotic groups of plants Regionalvegetation databases Ecological-coenotic forest type Indices of vegetation diversity for regional forest types Phytosociological releves Average species richness for the forest unit

  10. Database on 11000 vegetation sample plotsin mapped points of European Russian forests Regionalvegetation databases Phytosociological releves

  11. Dynamics of ground vegetation diversity EFIMOD runs Forest inventory data Tree species composition Regional vegetation databases Deadwood, litter, soil C and N pools Ecological-coenotic forest type Ecological-coenotic forest type Dominant tree species Dominant tree species Dominant ecological-coenotic group Dominant ecological-coenotic group Average species richness for the forest unit Average species richness for the forest unit Step n Step 1

  12. BioCalc - a software for dynamic analysis of forest ground vegetation diversity

  13. BioCalc input data · tables of probabilistic distribution of the groups in ground vegetation according to the tree dominant and the forest site class · a correspondence tables between the forest types and ranks of plant species richness · a time series table of forest stand ecosystem parameters (results of the EFIMOD runs)

  14. Creation of rules for the switching the ecological-coenotic groups BioCalc user selects in an interactive mode from the time series tables the thresholds for a number of ecosystem parameters. These thresholds cause a change of the dominant ecological-coenotic group. The user can observe all values of any ecosystem parameter displayed graphically

  15. Creation of rules for the switching the ecological-coenotic groups If the values are digital, the graphic is built with the values in ascending order, which allows for an`easy detection of the thresholds

  16. BioCalck outputs Dynamics of · ground vegetation functional groups, · forest types, and · ranks of species diversity Transfer of the output results to the Common-GIS (Andrienko, Andrienko, 1999) for visual exploration of ground vegetation dynamics at the landscape level

  17. A case study experimental forestry“Russkii Les” (Moscow region) 273 ha 104 units Strategies of silvicultural regimes for 200 years time span ·natural development ·legal clear cutting ·selective cutting ·illegal clear cutting

  18. Case study rules of functional group switching (i) meadow group switched to boreal group when spruce began to dominate in overstorey (ii) any group switched to nemoral when oak and lime began to dominate in overstorey (iii) piny group switched to boreal group when deadwood overpassed the 1st threshold value (iv) any group switched to nitrophilous group when deadwood overpassed the second threshold value, and (v) nitrophilous group switched to nemoral group when deadwood fell below the 2nd threshold value

  19. Case study rules of functional group switching In the scenarios with clear cuttings: after the clear cutting, a dominant group was taken from a specially designed probabilistic table of the group distribution in ground vegetation designed for the after-clear-cutting conditions

  20. Tree dominant dynamics Natural development Selective cuttings Legal clear cuttings Illegal clear cuttings

  21. Tree dominant dynamics 200-year dynamics Legal selective cutting Natural development The beginning Legal clear cutting Illegal clear cutting

  22. Deadwood dynamics

  23. Functional group dynamics 200-year dynamics Legal selective cutting Natural development The beginning Legal clear cutting Illegal clear cutting

  24. Functional group dynamics Natural development Legal selective cuttings Legal clear cutting Illegal clear cutting

  25. Species diversity dynamics

  26. Species diversity dynamics 200-year dynamics Legal selective cutting Natural development The beginning Legal clear cutting Illegal clear cutting

  27. Regional level: Manturovsky forestry (Kostroma region), 120 000 ha, 3430 units I initial state, II legal clear-cutting, III natural development 50-year dynamics

  28. Conclusion The functional group approach was elaborated and tested for modelling the dynamics of forest ground vegetation diversity. The modelling results showed that cuttings support a higher ecosystem diversity of the area in comparison to the free forest development. However, the protective strategy leads to the higher species diversity in ground vegetation, if a free forest development has taken place for rather long time, e.g. more than 100 years in our study area.

  29. EFIMOD parameters for ground vegetation dynamics used tree composition deadwood in progressC and N soil pools in planlight soil moisture

  30. Thank you for your attention!

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